8 citations · 36 across the 12 of their papers we have counts for
9 papers · 1 filter
Fast Propagation is Better: Accelerating Single-Step Adversarial Training via Sampling Subnetworks
Xiaojun Jia, Jianshu Li, Jindong Gu +2
Adversarial training has shown promise in building robust models against adversarial examples. A major drawback of adversarial training is the computational overhead introduced by…
Revisiting and Exploring Efficient Fast Adversarial Training via LAW: Lipschitz Regularization and Auto Weight Averaging
Xiaojun Jia, Yuefeng Chen, Xiaofeng Mao +5
Fast Adversarial Training (FAT) not only improves the model robustness but also reduces the training cost of standard adversarial training. However, fast adversarial training often…
Inter-frame Accelerate Attack against Video Interpolation Models
Junpei Liao, Zhikai Chen, Liang Yi +3
Deep learning based video frame interpolation (VIF) method, aiming to synthesis the intermediate frames to enhance video quality, have been highly developed in the past few years.…
A Large-scale Multiple-objective Method for Black-box Attack against Object Detection
Siyuan Liang, Longkang Li, Yanbo Fan +4
Recent studies have shown that detectors based on deep models are vulnerable to adversarial examples, even in the black-box scenario where the attacker cannot access the model info…
Exploring Inconsistent Knowledge Distillation for Object Detection with Data Augmentation
Jiawei Liang, Siyuan Liang, Aishan Liu +3
Knowledge Distillation (KD) for object detection aims to train a compact detector by transferring knowledge from a teacher model. Since the teacher model perceives data in a way di…
Prior-Guided Adversarial Initialization for Fast Adversarial Training
Xiaojun Jia, Yong Zhang, Xingxing Wei +4
Fast adversarial training (FAT) effectively improves the efficiency of standard adversarial training (SAT). However, initial FAT encounters catastrophic overfitting, i.e.,the robus…
Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal
Xinwei Liu, Jian Liu, Yang Bai +4
As a common security tool, visible watermarking has been widely applied to protect copyrights of digital images. However, recent works have shown that visible watermarks can be rem…
LAS-AT: Adversarial Training with Learnable Attack Strategy
Xiaojun Jia, Yong Zhang, Baoyuan Wu +3
Adversarial training (AT) is always formulated as a minimax problem, of which the performance depends on the inner optimization that involves the generation of adversarial examples…
Parallel Rectangle Flip Attack: A Query-based Black-box Attack against Object Detection
Siyuan Liang, Baoyuan Wu, Yanbo Fan +2
Object detection has been widely used in many safety-critical tasks, such as autonomous driving. However, its vulnerability to adversarial examples has not been sufficiently studie…